4 papers · 1 filter
Perception-Aware Autonomous Exploration in Feature-Limited Environments
Moji Shi, Rajitha de Silva, Hang Yu +3
Autonomous exploration in unknown environments typically relies on onboard state estimation for localisation and mapping. Existing exploration methods primarily maximise coverage e…
Semantic Landmark Particle Filter for Robot Localisation in Vineyards
Rajitha de Silva, Jonathan Cox, James R. Heselden +3
Reliable localisation in vineyards is hindered by row-level perceptual aliasing: parallel crop rows produce nearly identical LiDAR observations, causing geometry-only and vision-ba…
Crop Spirals: Re-thinking the field layout for future robotic agriculture
Lakshan Lavan, Lanojithan Thiyagarasa, Udara Muthugala +1
Conventional linear crop layouts, optimised for tractors, hinder robotic navigation with tight turns, long travel distances, and perceptual aliasing. We propose a robot-centric squ…
Semantic-Aware Particle Filter for Reliable Vineyard Robot Localisation
Rajitha de Silva, Jonathan Cox, James R. Heselden +3
Accurate localisation is critical for mobile robots in structured outdoor environments, yet LiDAR-based methods often fail in vineyards due to repetitive row geometry and perceptua…